Unraveling disparities in county‐level dementia diagnosis prevalence across the United States
Six models tested predictors of county-level dementia diagnosis prevalence. Backward selection was the main model: seven variables, high accuracy (AUC = 0.84). Higher diabetes, uninsured rates, White race prevalence, and fast food linked to more dementia diagnoses. Larger households, higher elevation, and more smokers linked to less dementia diagnoses. Some predictors (e.g., elevation) likely act as proxies; collinearity limits causality.
Authors
- Christopher D. Anderson (ORCID: https://orcid.org/0000-0002-0053-2002)
- Jonathan Rosand (ORCID: https://orcid.org/0000-0002-1014-9138)
- Shadi R. Yaghi (ORCID: https://orcid.org/0000-0003-0031-1004)
- Guido J. Falcone (ORCID: https://orcid.org/0000-0002-6407-0302)
- Adam de Havenon (ORCID: https://orcid.org/0000-0001-8178-8597)
- Arman Fesharaki
- Lauren Littig (ORCID: https://orcid.org/0009-0005-7389-0328)
- Richa Sharma (ORCID: https://orcid.org/0000-0003-0462-661X)
- Kevin N. Sheth
- Erick Calvario
Institutions
- University of Utah (US)
- Brown University (US)
- Yale University (US)
- Massachusetts General Hospital (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz.70954
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- American Heart Association
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke